In households, e.g. electric (space) heating, fridge and freezer, boiler, lighting, consumer electronics, ventilation and air-conditioning often represent the biggest loads to the electricity network. In contrast, with industrial environments different large-scale processes and related machinery may naturally consume considerable amounts of energy including electricity. Equally in both scenarios, the energy consumption shall be accurately measured to enable, among other potential uses, appropriate, fair billing thereof, usually based on unit price without forgetting potential other price-affecting factors such as time of the day (tariff).
Contemporary solutions for keeping track of site-specific, such as plant or house-specific, electricity consumption are typically based on automatically functioning electricity meters that measure the amount of energy used by the local loads such as different electrical appliances mentioned above.
Generally, the electricity meters may, for example, phase-specifically monitor the associated voltages and currents to produce phase-specific and subsequently aggregate consumption figures. Power figures may be first obtained by measuring the instantaneous voltage and current, whereas an indication of the consumed energy is obtained as the time integral of power. For instance, the meters may be configured to measure energy consumption using kWh (kilowatt hour) or joules as units. Power demand may be measured e.g. in watts (W) and is often averaged over a predetermined period. Commercial and industrial electricity users are customarily billed on both consumption and (peak) demand basis, whereas residential users are charged for consumption only. More complex charging schemes require also more complex electricity meters.
Older electricity meters in use may still be electromechanical based on e.g. rotating aluminum disc sensitive to the consumed power and require manual reading by the personnel of the power company, for instance. More modern counterparts are, however, electronic incorporating microprocessor-based current/voltage analysis and often support remote reading (telemetry) by means of telephone lines, power lines or wireless communication technology, with reference to various AMR (Automatic Meter Reading) or RMR (Remote Meter Reading) systems. Further, different smart meters capable of e.g. power quality monitoring have been set forth.
There are also various portable energy monitors available, which can be used to check the energy consumption and related parameters regarding a single host device (load) by plugging the host device such as a consumer electronics device to the mains via the energy monitor.
Notwithstanding the obvious benefits the modern metering solutions offer in monitoring the electricity consumption, there still remains some room for improvements. Namely, it is a globally acknowledged fact that the electricity meters sometimes fail either completely or begin to register false readings during their life cycle even though specific attention on the measurement accuracy has been taken during the manufacturing of the meters and the related design rules and standards have been followed. As also the legal framework around electricity metering is continuously tightening and various countries have enacted laws or rules on securing the measuring accuracy of electricity consumption also in the long run, i.e. after the deployment of the measuring equipment, there's a growing need to provide applicable solution for such.
On system level, e.g. a power company may be capable of recognizing anomalies in electricity consumption when comparing e.g. monthly consumption figures of a monitored site relative to several passed months and e.g. the same month in previous year and maybe the year before. Additionally, several similar sites may be mutually compared to find anomalies such as statistically significant deviation between the registered electricity usage statistics. Based on a detected anomaly in the electricity consumption figures, meter malfunction may be certainly suspected as one possible explanation, but reaching even such a vague conclusion takes considerable amount of time.
Further in some occasions, random samples may be exploited for generally testing the installed electricity meters, which usually requires visiting a number of randomly picked sites, e.g. one of thousand, by the maintenance personnel equipped with the necessary testing gear. Alternatively, the personnel may be instructed to collect the meters for remote laboratory testing and to at least temporarily replace the taken away meter with a reserve unit. In the ultimate case, the tested, passed unit will be finally returned to the original site by the personnel. Such procedures require vast amounts of manual labor, are tedious and still a good number of faulty meters may remain in use, i.e. the obtained level of certainty is not satisfactory when fault-free, validated operation of basically every electricity meter, not just some percentage thereof, is desired.